The understanding of the biochemical synthetic pathways in the metabolism of animal or plant cells, including micro-organisms such as bacteria, fungi and algae, or mammalian cells, remains very rudimentary, even though the main synthetic pathways are known. To date, the determination of physiological states during growth, development or as a response to environmental stress is essentially limited to the study of individual target molecules such as, for example, RNA and proteins. However, changes in the mRNA or protein level or their activity can frequently not be correlated with changes in the metabolism or indeed with phenotypic functions.
Cellular constituents or metabolites are frequently analyzed directly either by specific enzymatic reactions, immunoassays or on the basis of chromatographic methods, which identify certain substances by their retention times or coelution with reference substances. As described in Katona, J. Chromatography 1999, 847, 91-102, most of the prior art only deals with the analysis of few, specific components, for example acids or sugars.
There have only been rudimentary attempts to demonstrate that metabolic products, or metabolites, constitute not only intermediates or end products, but also act as sensors and regulators. The analysis of complex metabolic profiles or of constituents in organisms is therefore of great importance in assigning gene functions, in the assessment of stress effects and, last but not least, in the assessment of the safety and value of genetically modified organisms.
To be able to study these relationships, however, it is generally necessary to study organic systems as detailed and reproducibly as possible under different conditions so that, for example genetic variabilities or various internal or external effects can be identified. This, however, necessarily requires the analysis of a large number of samples.
The most advanced aspect of the determination of complex metabolic profiles (irrespective of whether this determination is limited to various classes of substances, developmental stages or types of material, i.e. irrespective of whether it takes the form of metabolic fingerprinting, metabolic profiling or metabolomics) in diagnostic screens, which first profiles have also recently been described for plants (for a review see Trethewey, Curr. Opin. Plant. Biol. 1999, 2, 83-85). Thus, Sauter (ACS Symposium Series 1991, 443 (Synth. Chem. Agrochem. 2), American Chemical Society, Washington, D.C., 288-299) demonstrates the modification of constituents in barley following treatment with various herbicides. Between 100 and 200 signals were detected and identified with the aid of reference substances via their retention coefficients in gas chromatography (GC) or via gas chromatography/mass spectrometry analysis (GC/MS).
Fiehn, Nature Biotechnology 2000, 18, 1157-1161 describes the quantification of 326 substances in Arabidopsis thaliana leaf extracts. To compare four different genotypes, present plant samples were homogenized in a complicated procedure, extracted with 97% by volume of methanol, and, after addition of chloroform and water, a multi-step procedure gave a polar and an unpolar phase which were then analyzed by LC/MS and GC/MS (see also Fiehn, Anal. Chem. 2000, 72, 3573-3580; http://www-.mpimp-golm.mpg.de/fiehn/blatt-protokoll-e.html). Following a very similar method, Roessner, The Plant Journal 2000, 23, 131-142, extracts plant constituents with methanol and compare the profiles of polar metabolites of in-vitro potato plants and potato plants grown in soil.
Gilmour, Plant Physiology 2000, 124, 1854-1865 extracts sugar from lyophilized leaves of five different Arabidopsis species in 80% ethanol following incubation for 15 minutes at 80° C. and incubation overnight at 4° C. Strand, Plant Physiology 1999, 119, 1387-1397 extracts soluble sugars and starch twice in succession, likewise at 80° C. and for 30 minutes and in 80% ethanol with Hepes, pH 7.5. The material is then reextracted twice at this high temperature to improve the result of the extraction once with 50% ethanol/Hepes, pH 7.5, and once with Hepes, pH 7.5.
These methods described in the prior art only permit limited automation which, moreover, can only be realised in the form of a complex procedure. In particular the processing of large sample numbers, the determination of the effect of a variety of stress factors on the metabolism of the organisms or the observation of dynamic processes, which requires a continuous analysis of samples during windows which are often very short, require processes    (a) which are rapid, i.e. for example that fixing and analysis of the samples is effected within a short period of the sampling,    (b) which are highly reproducible, i.e. for example that an analysis carried out with a large number of different samples gives results within a very narrow error margin,    (c) which are simple to handle, i.e. for example that the process can be automated and does not require complex or laborious procedures,    (d) which are open, i.e. for example that a large number of substances can be analyzed, and/or    (e) which are sensitive, i.e. for example that the analysis identifies even small changes in substance concentrations and small amounts of substance.
With a larger number of samples, it is particularly necessary to ensure sample stability, and thus the reproducibility of the results. A comprehensive continuous analysis of biological material, for example animal samples or plant samples, or for example the interaction between a substance, or substances, and organisms in complex systems and their course over time is thus not possible with the prior-art processes.